neon-aqu-aos.mysite = 'PRLA'
See how many locations chl data is collected from
See how many locations chl data is collected from (variable Y axis)
Availability of chlorophyll AOS data for each flight date
| flightdate | aos_before | aos_after | days_before | days_after | min_days | meets_thresh1 | meets_thresh2 |
|---|---|---|---|---|---|---|---|
| 2016-06-29 | NA | 2019-07-11 | NA | 1107 | 1107 | FALSE | FALSE |
| 2017-06-21 | NA | 2019-07-11 | NA | 750 | 750 | FALSE | FALSE |
| 2017-06-26 | NA | 2019-07-11 | NA | 745 | 745 | FALSE | FALSE |
| 2019-07-26 | 2019-07-11 | 2019-09-10 | 15 | 46 | 15 | TRUE | TRUE |
| 2019-07-27 | 2019-07-11 | 2019-09-10 | 16 | 45 | 16 | TRUE | TRUE |
| 2019-07-30 | 2019-07-11 | 2019-09-10 | 19 | 42 | 19 | TRUE | TRUE |
| 2020-06-24 | 2020-06-15 | 2020-09-29 | 9 | 97 | 9 | TRUE | TRUE |
| 2020-06-26 | 2020-06-15 | 2020-09-29 | 11 | 95 | 11 | TRUE | TRUE |
| 2020-07-02 | 2020-06-15 | 2020-09-29 | 17 | 89 | 17 | TRUE | TRUE |
| flightdate | aos_match | days |
|---|---|---|
| 2019-07-26 | 2019-07-11 | 15 |
| 2019-07-27 | 2019-07-11 | 16 |
| 2019-07-30 | 2019-07-11 | 19 |
| 2020-06-24 | 2020-06-15 | 9 |
| 2020-06-26 | 2020-06-15 | 11 |
| 2020-07-02 | 2020-06-15 | 17 |
## [1] "microgramsPerLiter"
## [1] "condition ok"
These are the closest chl AOS values for each flight date
| aos_match | flightdate | days | pheophytin | chlorophyll a |
|---|---|---|---|---|
| 2019-07-11 | 2019-07-26 | 15 | 3.01 | 2.31 |
| 2019-07-11 | 2019-07-27 | 16 | 3.01 | 2.31 |
| 2019-07-11 | 2019-07-30 | 19 | 3.01 | 2.31 |
| 2020-06-15 | 2020-06-24 | 9 | 4.20 | 3.45 |
| 2020-06-15 | 2020-06-26 | 11 | 4.20 | 3.45 |
| 2020-06-15 | 2020-07-02 | 17 | 4.20 | 3.45 |
TO DO!!!!!
The EXO total algae sensor is a dual‐channel fluorometer that uses a 470nm excitation beam that excites chlorophyll a and a second 590 nm excitation beam that excites the phyocyanin accessory pigment found in blue‐green algae (cyanobacteria). Chlorophyll concentration is a biogeochemically relavant parameter that is readily available by remote sensing and can be can serve as a proxy for phytoplankton biomass and light attenuation (Oestreich et al., 2016, Ganju et al., 2014, Jaud et al., 2012)
Sensor chl data availability
| flightline_datetime | check_30day | check_10day | check_1day | check_12hr |
|---|---|---|---|---|
| 2016-06-29 15:45:47 | FALSE | FALSE | FALSE | FALSE |
| 2016-06-29 15:52:09 | FALSE | FALSE | FALSE | FALSE |
| 2016-06-29 17:22:24 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-21 20:58:28 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 15:33:21 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 16:04:51 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 16:11:11 | FALSE | FALSE | FALSE | FALSE |
| 2019-07-26 15:20:23 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-26 16:22:11 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-26 22:09:25 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-27 15:27:04 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-30 15:34:20 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 17:36:27 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 16:26:15 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 16:18:44 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-26 19:28:06 | TRUE | TRUE | TRUE | FALSE |
| 2020-07-02 17:14:10 | TRUE | TRUE | FALSE | FALSE |
zoo::rollapply.tsibbleGet the moving average value closet to flight time.
| collectDateTime | datetime | chl5min | chl_ma01 | chl_ma03 | chl_ma04 | chl_ma04u | chl_ma06 | chl_ma12 |
|---|---|---|---|---|---|---|---|---|
| 2019-07-26 15:20:23 | 2019-07-26 15:20:00 | 5.83 | 6.245 | 6.285 | 6.290 | 6.312174 | 6.350 | 6.610 |
| 2019-07-26 16:22:11 | 2019-07-26 16:20:00 | 6.70 | 6.175 | 6.285 | 6.310 | 6.327500 | 6.425 | 6.610 |
| 2019-07-26 22:09:25 | 2019-07-26 22:10:00 | 7.47 | 7.665 | 7.735 | 7.695 | 7.881042 | 7.660 | 7.650 |
| 2019-07-27 15:27:04 | 2019-07-27 15:25:00 | 8.16 | 8.195 | 8.380 | 8.400 | 8.477083 | 8.455 | 8.655 |
| 2019-07-30 15:34:20 | 2019-07-30 15:35:00 | 18.12 | 17.850 | 17.460 | 17.460 | 17.539130 | 17.860 | 19.670 |
zoo::rollapply.tsibbleGet the moving average value closet to flight time
| collectDateTime | datetime | chl5min | chl_ma01 | chl_ma03 | chl_ma04 | chl_ma04u | chl_ma06 | chl_ma12 |
|---|---|---|---|---|---|---|---|---|
| 2020-06-24 17:36:27 | 2020-06-24 17:35:00 | 2.54 | 2.320 | 2.48 | 2.545 | 2.638333 | 2.715 | 3.150 |
| 2020-06-24 16:26:15 | 2020-06-24 16:25:00 | 2.74 | 2.565 | 2.56 | 2.565 | 2.581875 | 2.680 | 3.165 |
| 2020-06-24 16:18:44 | 2020-06-24 16:20:00 | 2.54 | 2.565 | 2.56 | 2.585 | 2.587917 | 2.680 | 3.175 |
| 2020-06-26 19:28:06 | 2020-06-26 19:30:00 | NA | NA | NA | NA | NaN | NA | NA |
| 2020-07-02 17:14:10 | 2020-07-02 17:15:00 | NA | NA | NA | NA | NaN | NA | NA |
chla_df date and times with the aop/ais matching function to determine which sampling dates have sensor data from same day around time of sampling.already sort of done for suna data… follow this pattern
| aos_datetime | check_3day | check_1day | check_6hr | check_1hr |
|---|---|---|---|---|
| 2019-07-11 13:53:00 | TRUE | TRUE | TRUE | TRUE |
| 2019-09-10 13:37:00 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-15 15:09:00 | TRUE | TRUE | TRUE | TRUE |
| 2020-09-29 13:21:00 | FALSE | FALSE | FALSE | FALSE |
| 2021-04-20 14:40:00 | FALSE | FALSE | FALSE | FALSE |
| aos_datetime | check_3day | check_1day | check_6hr | check_1hr |
|---|---|---|---|---|
| 2019-07-11 13:53:00 | TRUE | TRUE | TRUE | TRUE |
| 2019-09-10 13:37:00 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-15 15:09:00 | TRUE | TRUE | TRUE | TRUE |
| collect_date | pheophytin | chla | chl_tot |
|---|---|---|---|
| 2019-07-11 | 3.01 | 2.31 | 5.32 |
| 2019-09-10 | 3.08 | 2.79 | 5.87 |
| 2020-06-15 | 4.20 | 3.45 | 7.65 |
| 2020-09-29 | 72.40 | 124.44 | 196.84 |
| 2021-04-20 | 21.38 | 20.03 | 41.41 |
Compare AOS and AIS
EPA Method description:
The UVA procedure requires that the sample be passed through a 0.45 um filter and transferred to quartz cell. It is then placed in a spectrophotometer to measure the UV absorbance at 254 nm and reported in cm -1.
The SUVA procedure requires both the DOC and UVA measurement. The SUVA is then calculated by dividing the UV absorbance of the sample (in cm -1) by the DOC of the sample (in mg/L) and then multiplying by 100 cm/M. SUVA is reported in units of L/mg-M. The formula for the SUVA may be found in Section 12.2.
Ignoring data before 2016
## Warning: Removed 2 rows containing missing values (geom_point).
Correct older UV Absorbance wavelengths from 250 to 254, assuming all 250 nm should be 254.
swchem_site_df <- swchem_site_df %>%
dplyr::mutate(analyte = dplyr::case_when(analyte == 'UV Absorbance (250 nm)' ~
'UV Absorbance (254 nm)', TRUE ~ analyte))
## Warning: Removed 2 rows containing missing values (geom_point).
How much does SUVA 254/280 ratio change?
How much does organic carbon dissolved proportion change?
Adjusts sample IDs in a new column to group together raw and filtered, while keeping track of duplicates
## Warning: Removed 11 rows containing missing values (geom_point).
Match DOM AOS and AOP data
Need to do this separately for each analyte because they arent always all reported.
These are the closest DOC values (mg/L) for each flight date
| flightdate | aos_before | aos_after | days_before | days_after | min_days | meets_thresh1 | meets_thresh2 |
|---|---|---|---|---|---|---|---|
| 2016-06-29 | 2014-06-19 | 2016-10-19 | 741 | 112 | 112 | FALSE | FALSE |
| 2017-06-21 | 2017-06-08 | 2017-07-06 | 13 | 15 | 13 | TRUE | TRUE |
| 2017-06-26 | 2017-06-08 | 2017-07-06 | 18 | 10 | 10 | TRUE | TRUE |
| 2019-07-26 | 2019-07-01 | 2019-08-06 | 25 | 11 | 11 | TRUE | TRUE |
| 2019-07-27 | 2019-07-01 | 2019-08-06 | 26 | 10 | 10 | TRUE | TRUE |
| 2019-07-30 | 2019-07-01 | 2019-08-06 | 29 | 7 | 7 | TRUE | TRUE |
| 2020-06-24 | 2020-06-09 | 2020-08-04 | 15 | 41 | 15 | TRUE | TRUE |
| 2020-06-26 | 2020-06-09 | 2020-08-04 | 17 | 39 | 17 | TRUE | TRUE |
| 2020-07-02 | 2020-06-09 | 2020-08-04 | 23 | 33 | 23 | TRUE | TRUE |
| flightdate | aos_match | days |
|---|---|---|
| 2017-06-21 | 2017-06-08 | 13 |
| 2017-06-26 | 2017-07-06 | 10 |
| 2019-07-26 | 2019-08-06 | 11 |
| 2019-07-27 | 2019-08-06 | 10 |
| 2019-07-30 | 2019-08-06 | 7 |
| 2020-06-24 | 2020-06-09 | 15 |
| 2020-06-26 | 2020-06-09 | 17 |
| 2020-07-02 | 2020-06-09 | 23 |
| aos_match | flightdate | days | DOC |
|---|---|---|---|
| 2017-06-08 | 2017-06-21 | 13 | 29.97 |
| 2017-07-06 | 2017-06-26 | 10 | 31.68, 31.81, 32.11 |
| 2019-08-06 | 2019-07-26 | 11 | 35.01 |
| 2019-08-06 | 2019-07-27 | 10 | 35.01 |
| 2019-08-06 | 2019-07-30 | 7 | 35.01 |
| 2020-06-09 | 2020-06-24 | 15 | 26.72 |
| 2020-06-09 | 2020-06-26 | 17 | 26.72 |
| 2020-06-09 | 2020-07-02 | 23 | 26.72 |
These are the closest UV abs values (per 1 cm) for each flight date
| flightdate | aos_before | aos_after | days_before | days_after | min_days | meets_thresh1 | meets_thresh2 |
|---|---|---|---|---|---|---|---|
| 2016-06-29 | NA | 2016-10-19 | NA | 112 | 112 | FALSE | FALSE |
| 2017-06-21 | 2017-06-08 | 2017-07-06 | 13 | 15 | 13 | TRUE | TRUE |
| 2017-06-26 | 2017-06-08 | 2017-07-06 | 18 | 10 | 10 | TRUE | TRUE |
| 2019-07-26 | 2019-07-01 | 2019-08-06 | 25 | 11 | 11 | TRUE | TRUE |
| 2019-07-27 | 2019-07-01 | 2019-08-06 | 26 | 10 | 10 | TRUE | TRUE |
| 2019-07-30 | 2019-07-01 | 2019-08-06 | 29 | 7 | 7 | TRUE | TRUE |
| 2020-06-24 | 2019-12-04 | 2020-08-04 | 203 | 41 | 41 | FALSE | TRUE |
| 2020-06-26 | 2019-12-04 | 2020-08-04 | 205 | 39 | 39 | FALSE | TRUE |
| 2020-07-02 | 2019-12-04 | 2020-08-04 | 211 | 33 | 33 | FALSE | TRUE |
| flightdate | aos_match | days |
|---|---|---|
| 2017-06-21 | 2017-06-08 | 13 |
| 2017-06-26 | 2017-07-06 | 10 |
| 2019-07-26 | 2019-08-06 | 11 |
| 2019-07-27 | 2019-08-06 | 10 |
| 2019-07-30 | 2019-08-06 | 7 |
| 2020-06-24 | 2020-08-04 | 41 |
| 2020-06-26 | 2020-08-04 | 39 |
| 2020-07-02 | 2020-08-04 | 33 |
| aos_match | flightdate | days | UV Absorbance (254 nm) |
|---|---|---|---|
| 2017-06-08 | 2017-06-21 | 13 | 0.5578 |
| 2017-07-06 | 2017-06-26 | 10 | 0.5566, 0.5710, 0.5653 |
| 2019-08-06 | 2019-07-26 | 11 | 0.7538 |
| 2019-08-06 | 2019-07-27 | 10 | 0.7538 |
| 2019-08-06 | 2019-07-30 | 7 | 0.7538 |
| 2020-08-04 | 2020-06-24 | 41 | 0.5646 |
| 2020-08-04 | 2020-06-26 | 39 | 0.5646 |
| 2020-08-04 | 2020-07-02 | 33 | 0.5646 |
| flightdate | aos_before | aos_after | days_before | days_after | min_days | meets_thresh1 | meets_thresh2 |
|---|---|---|---|---|---|---|---|
| 2016-06-29 | NA | 2016-10-19 | NA | 112 | 112 | FALSE | FALSE |
| 2017-06-21 | 2017-06-08 | 2017-07-06 | 13 | 15 | 13 | TRUE | TRUE |
| 2017-06-26 | 2017-06-08 | 2017-07-06 | 18 | 10 | 10 | TRUE | TRUE |
| 2019-07-26 | 2019-07-01 | 2019-08-06 | 25 | 11 | 11 | TRUE | TRUE |
| 2019-07-27 | 2019-07-01 | 2019-08-06 | 26 | 10 | 10 | TRUE | TRUE |
| 2019-07-30 | 2019-07-01 | 2019-08-06 | 29 | 7 | 7 | TRUE | TRUE |
| 2020-06-24 | 2019-12-04 | 2020-08-04 | 203 | 41 | 41 | FALSE | TRUE |
| 2020-06-26 | 2019-12-04 | 2020-08-04 | 205 | 39 | 39 | FALSE | TRUE |
| 2020-07-02 | 2019-12-04 | 2020-08-04 | 211 | 33 | 33 | FALSE | TRUE |
| flightdate | aos_match | days |
|---|---|---|
| 2017-06-21 | 2017-06-08 | 13 |
| 2017-06-26 | 2017-07-06 | 10 |
| 2019-07-26 | 2019-08-06 | 11 |
| 2019-07-27 | 2019-08-06 | 10 |
| 2019-07-30 | 2019-08-06 | 7 |
| 2020-06-24 | 2020-08-04 | 41 |
| 2020-06-26 | 2020-08-04 | 39 |
| 2020-07-02 | 2020-08-04 | 33 |
| aos_match | flightdate | days | UV Absorbance (280 nm) |
|---|---|---|---|
| 2017-06-08 | 2017-06-21 | 13 | 0.2876 |
| 2017-07-06 | 2017-06-26 | 10 | 0.2887, 0.2961, 0.2950 |
| 2019-08-06 | 2019-07-26 | 11 | 0.3852 |
| 2019-08-06 | 2019-07-27 | 10 | 0.3852 |
| 2019-08-06 | 2019-07-30 | 7 | 0.3852 |
| 2020-08-04 | 2020-06-24 | 41 | 0.3118 |
| 2020-08-04 | 2020-06-26 | 39 | 0.3118 |
| 2020-08-04 | 2020-07-02 | 33 | 0.3118 |
| flightdate | aos_before | aos_after | days_before | days_after | min_days | meets_thresh1 | meets_thresh2 |
|---|---|---|---|---|---|---|---|
| 2016-06-29 | 2014-06-19 | 2016-10-19 | 741 | 112 | 112 | FALSE | FALSE |
| 2017-06-21 | 2017-06-08 | 2017-07-06 | 13 | 15 | 13 | TRUE | TRUE |
| 2017-06-26 | 2017-06-08 | 2017-07-06 | 18 | 10 | 10 | TRUE | TRUE |
| 2019-07-26 | 2019-07-01 | 2019-08-06 | 25 | 11 | 11 | TRUE | TRUE |
| 2019-07-27 | 2019-07-01 | 2019-08-06 | 26 | 10 | 10 | TRUE | TRUE |
| 2019-07-30 | 2019-07-01 | 2019-08-06 | 29 | 7 | 7 | TRUE | TRUE |
| 2020-06-24 | 2020-06-09 | 2020-06-30 | 15 | 6 | 6 | TRUE | TRUE |
| 2020-06-26 | 2020-06-09 | 2020-06-30 | 17 | 4 | 4 | TRUE | TRUE |
| 2020-07-02 | 2020-06-30 | 2020-08-04 | 2 | 33 | 2 | TRUE | TRUE |
| flightdate | aos_match | days |
|---|---|---|
| 2017-06-21 | 2017-06-08 | 13 |
| 2017-06-26 | 2017-07-06 | 10 |
| 2019-07-26 | 2019-08-06 | 11 |
| 2019-07-27 | 2019-08-06 | 10 |
| 2019-07-30 | 2019-08-06 | 7 |
| 2020-06-24 | 2020-06-30 | 6 |
| 2020-06-26 | 2020-06-30 | 4 |
| 2020-07-02 | 2020-06-30 | 2 |
| aos_match | flightdate | days | TOC |
|---|---|---|---|
| 2017-06-08 | 2017-06-21 | 13 | 34.12 |
| 2017-07-06 | 2017-06-26 | 10 | 37.87, 38.11, 38.82 |
| 2019-08-06 | 2019-07-26 | 11 | 36.05 |
| 2019-08-06 | 2019-07-27 | 10 | 36.05 |
| 2019-08-06 | 2019-07-30 | 7 | 36.05 |
| 2020-06-30 | 2020-06-24 | 6 | 26.05, 26.49, 26.18 |
| 2020-06-30 | 2020-06-26 | 4 | 26.05, 26.49, 26.18 |
| 2020-06-30 | 2020-07-02 | 2 | 26.05, 26.49, 26.18 |
| flightdate | aos_before | aos_after | days_before | days_after | min_days | meets_thresh1 | meets_thresh2 |
|---|---|---|---|---|---|---|---|
| 2016-06-29 | 2014-06-19 | 2016-10-19 | 741 | 112 | 112 | FALSE | FALSE |
| 2017-06-21 | 2017-06-08 | 2017-07-06 | 13 | 15 | 13 | TRUE | TRUE |
| 2017-06-26 | 2017-06-08 | 2017-07-06 | 18 | 10 | 10 | TRUE | TRUE |
| 2019-07-26 | 2019-07-01 | 2019-08-06 | 25 | 11 | 11 | TRUE | TRUE |
| 2019-07-27 | 2019-07-01 | 2019-08-06 | 26 | 10 | 10 | TRUE | TRUE |
| 2019-07-30 | 2019-07-01 | 2019-08-06 | 29 | 7 | 7 | TRUE | TRUE |
| 2020-06-24 | 2019-12-04 | 2021-05-04 | 203 | 314 | 203 | FALSE | FALSE |
| 2020-06-26 | 2019-12-04 | 2021-05-04 | 205 | 312 | 205 | FALSE | FALSE |
| 2020-07-02 | 2019-12-04 | 2021-05-04 | 211 | 306 | 211 | FALSE | FALSE |
| flightdate | aos_match | days |
|---|---|---|
| 2017-06-21 | 2017-06-08 | 13 |
| 2017-06-26 | 2017-07-06 | 10 |
| 2019-07-26 | 2019-08-06 | 11 |
| 2019-07-27 | 2019-08-06 | 10 |
| 2019-07-30 | 2019-08-06 | 7 |
| aos_match | flightdate | days | Fe |
|---|---|---|---|
| 2017-06-08 | 2017-06-21 | 13 | 5e-04 |
| 2017-07-06 | 2017-06-26 | 10 | 5e-04, 5e-04, 5e-04 |
| 2019-08-06 | 2019-07-26 | 11 | 0.01 |
| 2019-08-06 | 2019-07-27 | 10 | 0.01 |
| 2019-08-06 | 2019-07-30 | 7 | 0.01 |
The EXO fDOM sensor is a fluorometer with a single excitation/emission pair (365nm/480nm) used to detect the fluorescent fraction of the chromophoric DOM when exposed to near‐UV light. Because of the impacts of temperature and water column absorbance (from a combination of dissolved and particulate compounds) on these readings corrections must be applied to the calibrated data.
| flightline_datetime | check_30day | check_10day | check_1day | check_12hr |
|---|---|---|---|---|
| 2016-06-29 15:45:47 | FALSE | FALSE | FALSE | FALSE |
| 2016-06-29 15:52:09 | FALSE | FALSE | FALSE | FALSE |
| 2016-06-29 17:22:24 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-21 20:58:28 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 15:33:21 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 16:04:51 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 16:11:11 | FALSE | FALSE | FALSE | FALSE |
| 2019-07-26 15:20:23 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-26 16:22:11 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-26 22:09:25 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-27 15:27:04 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-30 15:34:20 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 17:36:27 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 16:26:15 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 16:18:44 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-26 19:28:06 | TRUE | TRUE | TRUE | FALSE |
| 2020-07-02 17:14:10 | TRUE | TRUE | FALSE | FALSE |
## Warning: Removed 3170 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## Warning: Removed 8658 rows containing missing values (geom_point).
## Warning: Removed 2552 rows containing missing values (geom_point).
## Warning: Removed 444 row(s) containing missing values (geom_path).
## Warning: Removed 444 rows containing missing values (geom_point).
## Warning: Removed 4737 rows containing missing values (geom_point).
zoo::rollapply.tsibbleGet the moving average value closet to flight time.
| collectDateTime | datetime | fdom5min | ma01 | ma03 | ma04 | ma04u | ma06 | ma12 |
|---|---|---|---|---|---|---|---|---|
| 2019-07-26 15:20:23 | 2019-07-26 15:20:00 | 109.76 | 109.620 | 109.620 | 109.630 | 109.6151 | 109.630 | 109.63 |
| 2019-07-26 16:22:11 | 2019-07-26 16:20:00 | 109.22 | 109.260 | 109.260 | 109.260 | 109.2767 | 109.260 | 109.26 |
| 2019-07-26 22:09:25 | 2019-07-26 22:10:00 | 108.23 | 108.075 | 108.065 | 108.065 | 108.0837 | 108.070 | 108.09 |
| 2019-07-27 15:27:04 | 2019-07-27 15:25:00 | 105.65 | 105.760 | 105.745 | 105.745 | 105.7490 | 105.745 | 105.80 |
| 2019-07-30 15:34:20 | 2019-07-30 15:35:00 | 100.23 | 100.380 | 100.350 | 100.310 | 100.2890 | 100.340 | 100.35 |
zoo::rollapply.tsibbleGet the moving average value closet to flight time.
| collectDateTime | datetime | fdom5min | ma01 | ma03 | ma04 | ma04u | ma06 | ma12 |
|---|---|---|---|---|---|---|---|---|
| 2020-06-24 17:36:27 | 2020-06-24 17:35:00 | 69.59 | 69.625 | 69.700 | 69.730 | 69.53479 | 69.865 | 70.200 |
| 2020-06-24 16:26:15 | 2020-06-24 16:25:00 | 70.02 | 69.855 | 69.880 | 69.880 | 69.94437 | 69.850 | 70.105 |
| 2020-06-24 16:18:44 | 2020-06-24 16:20:00 | 69.73 | 69.945 | 69.955 | 69.955 | 69.96188 | 69.850 | 70.105 |
| 2020-06-26 19:28:06 | 2020-06-26 19:30:00 | NA | NA | NA | NA | NaN | NA | NA |
| 2020-07-02 17:14:10 | 2020-07-02 17:15:00 | NA | NA | NA | NA | NaN | NA | NA |
swchem_site_df in matching aop/ais functionTO DO!!!!
Data from all locations at site
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
sm_site_df <- sm_site_df %>%
dplyr::filter(namedLocation %in% my_loc)
## Warning: Transformation introduced infinite values in continuous y-axis
## Warning: Transformation introduced infinite values in continuous y-axis
How much does TDS/TSS change?
## Warning: Removed 1 row(s) containing missing values (geom_path).
## Warning: Removed 2 rows containing missing values (geom_point).
Match sediment aos to aop dates
source('R/match-aop-aos.R')
sm_match_list <- match_aop_aos(mysite_dates, sm_site_df, 'collect_date')
knitr::kable(sm_match_list$dates)
| flightdate | aos_before | aos_after | days_before | days_after | min_days | meets_thresh1 | meets_thresh2 |
|---|---|---|---|---|---|---|---|
| 2016-06-29 | 2014-06-19 | 2016-10-19 | 741 | 112 | 112 | FALSE | FALSE |
| 2017-06-21 | 2017-06-08 | 2017-07-06 | 13 | 15 | 13 | TRUE | TRUE |
| 2017-06-26 | 2017-06-08 | 2017-07-06 | 18 | 10 | 10 | TRUE | TRUE |
| 2019-07-26 | 2019-07-01 | 2019-08-06 | 25 | 11 | 11 | TRUE | TRUE |
| 2019-07-27 | 2019-07-01 | 2019-08-06 | 26 | 10 | 10 | TRUE | TRUE |
| 2019-07-30 | 2019-07-01 | 2019-08-06 | 29 | 7 | 7 | TRUE | TRUE |
| 2020-06-24 | 2019-12-04 | 2021-05-04 | 203 | 314 | 203 | FALSE | FALSE |
| 2020-06-26 | 2019-12-04 | 2021-05-04 | 205 | 312 | 205 | FALSE | FALSE |
| 2020-07-02 | 2019-12-04 | 2021-05-04 | 211 | 306 | 211 | FALSE | FALSE |
knitr::kable(sm_match_list$matches)
| flightdate | aos_match | days |
|---|---|---|
| 2017-06-21 | 2017-06-08 | 13 |
| 2017-06-26 | 2017-07-06 | 10 |
| 2019-07-26 | 2019-08-06 | 11 |
| 2019-07-27 | 2019-08-06 | 10 |
| 2019-07-30 | 2019-08-06 | 7 |
These are the closest in time ground-based measurements of TDS (mg/L) and TSS (mg/L)
| aos_match | flightdate | days | TDS | TSS | TSS - Dry Mass |
|---|---|---|---|---|---|
| 2017-06-08 | 2017-06-21 | 13 | 910.1 | 32 | 800 |
| 2017-07-06 | 2017-06-26 | 10 | 885.62, 887.64, 891.23 | 10, 9, 9 | 900, 900, 1000 |
| 2019-08-06 | 2019-07-26 | 11 | 744.6 | 10 | 500 |
| 2019-08-06 | 2019-07-27 | 10 | 744.6 | 10 | 500 |
| 2019-08-06 | 2019-07-30 | 7 | 744.6 | 10 | 500 |
The EXO turbidity sensor employs a near‐IR light source (~780 ‐ 900 nm) and detects scattering at 90 degrees of the incident beam.
| flightline_datetime | check_30day | check_10day | check_1day | check_12hr |
|---|---|---|---|---|
| 2016-06-29 15:45:47 | FALSE | FALSE | FALSE | FALSE |
| 2016-06-29 15:52:09 | FALSE | FALSE | FALSE | FALSE |
| 2016-06-29 17:22:24 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-21 20:58:28 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 15:33:21 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 16:04:51 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 16:11:11 | FALSE | FALSE | FALSE | FALSE |
| 2019-07-26 15:20:23 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-26 16:22:11 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-26 22:09:25 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-27 15:27:04 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-30 15:34:20 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 17:36:27 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 16:26:15 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 16:18:44 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-26 19:28:06 | TRUE | TRUE | TRUE | FALSE |
| 2020-07-02 17:14:10 | TRUE | TRUE | FALSE | FALSE |
## Warning: Removed 8537 row(s) containing missing values (geom_path).
## Warning: Removed 8658 rows containing missing values (geom_point).
## Warning: Removed 2438 row(s) containing missing values (geom_path).
## Warning: Removed 2552 rows containing missing values (geom_point).
## Warning: Removed 444 row(s) containing missing values (geom_path).
## Warning: Removed 444 rows containing missing values (geom_point).
## Warning: Removed 4737 row(s) containing missing values (geom_path).
## Warning: Removed 4737 rows containing missing values (geom_point).
zoo::rollapply.tsibbleGet the moving average value closet to flight time.
| collectDateTime | datetime | turb5min | ma01 | ma03 | ma04 | ma04u | ma06 | ma12 |
|---|---|---|---|---|---|---|---|---|
| 2019-07-26 15:20:23 | 2019-07-26 15:20:00 | 2.09 | 2.170 | 2.170 | 2.175 | 2.228913 | 2.180 | 2.240 |
| 2019-07-26 16:22:11 | 2019-07-26 16:20:00 | 2.17 | 2.205 | 2.230 | 2.240 | 2.326667 | 2.245 | 2.290 |
| 2019-07-26 22:09:25 | 2019-07-26 22:10:00 | 3.98 | 3.185 | 3.140 | 3.125 | 3.129167 | 3.080 | 2.925 |
| 2019-07-27 15:27:04 | 2019-07-27 15:25:00 | 3.62 | 2.985 | 2.930 | 2.910 | 2.942917 | 2.790 | 2.600 |
| 2019-07-30 15:34:20 | 2019-07-30 15:35:00 | 2.75 | 2.770 | 2.795 | 2.820 | 2.921591 | 2.820 | 2.820 |
zoo::rollapply.tsibbleGet the moving average value closet to flight time.
| collectDateTime | datetime | turb5min | ma01 | ma03 | ma04 | ma04u | ma06 | ma12 |
|---|---|---|---|---|---|---|---|---|
| 2020-06-24 17:36:27 | 2020-06-24 17:35:00 | 1.91 | 1.865 | 1.820 | 1.865 | 3.284375 | 1.845 | 1.9 |
| 2020-06-24 16:26:15 | 2020-06-24 16:25:00 | 1.51 | 1.795 | 1.875 | 1.840 | 2.687708 | 1.875 | 1.9 |
| 2020-06-24 16:18:44 | 2020-06-24 16:20:00 | 1.93 | 1.795 | 1.875 | 1.815 | 2.677292 | 1.875 | 1.9 |
| 2020-06-26 19:28:06 | 2020-06-26 19:30:00 | NA | NA | NA | NA | NaN | NA | NA |
| 2020-07-02 17:14:10 | 2020-07-02 17:15:00 | NA | NA | NA | NA | NaN | NA | NA |
TO DO!!!!
| flightline_datetime | check_30day | check_10day | check_1day | check_12hr |
|---|---|---|---|---|
| 2016-06-29 15:45:47 | FALSE | FALSE | FALSE | FALSE |
| 2016-06-29 15:52:09 | FALSE | FALSE | FALSE | FALSE |
| 2016-06-29 17:22:24 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-21 20:58:28 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 15:33:21 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 16:04:51 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-26 16:11:11 | FALSE | FALSE | FALSE | FALSE |
| 2019-07-26 15:20:23 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-26 16:22:11 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-26 22:09:25 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-27 15:27:04 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-30 15:34:20 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 17:36:27 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 16:26:15 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 16:18:44 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-26 19:28:06 | TRUE | TRUE | TRUE | TRUE |
| 2020-07-02 17:14:10 | TRUE | TRUE | TRUE | TRUE |
| flightline_datetime | check_30day | check_10day | check_1day | check_12hr |
|---|---|---|---|---|
| 2019-07-26 15:20:23 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-26 16:22:11 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-26 22:09:25 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-27 15:27:04 | TRUE | TRUE | TRUE | TRUE |
| 2019-07-30 15:34:20 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 17:36:27 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 16:26:15 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-24 16:18:44 | TRUE | TRUE | TRUE | TRUE |
| 2020-06-26 19:28:06 | TRUE | TRUE | TRUE | TRUE |
| 2020-07-02 17:14:10 | TRUE | TRUE | TRUE | TRUE |
| flightline_datetime | check_1day | interval3_start | interval3_end |
|---|---|---|---|
| 2019-07-26 15:20:23 | TRUE | 2019-07-23 | 2019-07-29 |
| 2019-07-26 16:22:11 | TRUE | 2019-07-23 | 2019-07-29 |
| 2019-07-26 22:09:25 | TRUE | 2019-07-23 | 2019-07-29 |
| 2019-07-27 15:27:04 | TRUE | 2019-07-24 | 2019-07-30 |
| 2019-07-30 15:34:20 | TRUE | 2019-07-27 | 2019-08-02 |
| 2020-06-24 17:36:27 | TRUE | 2020-06-21 | 2020-06-27 |
| 2020-06-24 16:26:15 | TRUE | 2020-06-21 | 2020-06-27 |
| 2020-06-24 16:18:44 | TRUE | 2020-06-21 | 2020-06-27 |
| 2020-06-26 19:28:06 | TRUE | 2020-06-23 | 2020-06-29 |
| 2020-07-02 17:14:10 | TRUE | 2020-06-29 | 2020-07-05 |
NEON-L0-SUNA/AOP-dates/{mysite}/{mysite}-103-2020.csvprocess-L0-SUNA in processing project## Rows: 803
## Columns: 9
## Delimiter: ","
## dbl [8]: mean_abs254, sd_abs254, n_abs254, se_abs254, mean_abs350, sd_abs350, n_abs350,...
## dttm [1]: burst_id
##
## Use `spec()` to retrieve the guessed column specification
## Pass a specification to the `col_types` argument to quiet this message
| collectDateTime | datetime | mean_abs254 | abs254_ma01 | abs254_ma03 | abs254_ma04 | abs254_ma04u | abs254_ma06 | abs254_ma12 |
|---|---|---|---|---|---|---|---|---|
| 2019-07-26 15:20:23 | 2019-07-26 15:15:00 | 0.7239778 | 0.7223167 | 0.7223167 | 0.7223500 | 0.7245560 | 0.7223500 | 0.7219900 |
| 2019-07-26 16:22:11 | 2019-07-26 16:15:00 | 0.7213222 | 0.7213500 | 0.7219522 | 0.7219522 | 0.7234967 | 0.7219522 | 0.7217889 |
| 2019-07-26 22:09:25 | 2019-07-26 22:15:00 | 0.7212750 | 0.7201167 | 0.7181789 | 0.7181789 | 0.7174843 | 0.7181789 | 0.7181800 |
| 2019-07-27 15:27:04 | 2019-07-27 15:30:00 | 0.6946000 | 0.6943750 | 0.6928211 | 0.6925200 | 0.6904142 | 0.6928211 | 0.6931222 |
| 2019-07-30 15:34:20 | 2019-07-30 15:30:00 | 0.6522333 | 0.6523500 | 0.6522917 | 0.6531444 | 0.6535957 | 0.6559706 | 0.6577222 |
| collectDateTime | datetime | mean_abs350 | abs350_ma01 | abs350_ma03 | abs350_ma04 | abs350_ma04u | abs350_ma06 | abs350_ma12 |
|---|---|---|---|---|---|---|---|---|
| 2019-07-26 15:20:23 | 2019-07-26 15:15:00 | 0.1960778 | 0.1944944 | 0.1944944 | 0.1944944 | 0.1966453 | 0.1944944 | 0.1938222 |
| 2019-07-26 16:22:11 | 2019-07-26 16:15:00 | 0.1936000 | 0.1936050 | 0.1936050 | 0.1936050 | 0.1953644 | 0.1936050 | 0.1930600 |
| 2019-07-26 22:09:25 | 2019-07-26 22:15:00 | 0.1911556 | 0.1904989 | 0.1902956 | 0.1902956 | 0.1886990 | 0.1902956 | 0.1901800 |
| 2019-07-27 15:27:04 | 2019-07-27 15:30:00 | 0.1660222 | 0.1659350 | 0.1653950 | 0.1653000 | 0.1635622 | 0.1653950 | 0.1654900 |
| 2019-07-30 15:34:20 | 2019-07-30 15:30:00 | 0.1245444 | 0.1245444 | 0.1242889 | 0.1257833 | 0.1268550 | 0.1278417 | 0.1314700 |
## Rows: 755
## Columns: 9
## Delimiter: ","
## dbl [8]: mean_abs254, sd_abs254, n_abs254, se_abs254, mean_abs350, sd_abs350, n_abs350,...
## dttm [1]: burst_id
##
## Use `spec()` to retrieve the guessed column specification
## Pass a specification to the `col_types` argument to quiet this message
| collectDateTime | datetime | mean_abs254 | abs254_ma01 | abs254_ma03 | abs254_ma04 | abs254_ma04u | abs254_ma06 | abs254_ma12 |
|---|---|---|---|---|---|---|---|---|
| 2020-06-24 17:36:27 | 2020-06-24 17:30:00 | 0.4602 | 0.4606 | 0.4606 | 0.4607 | 0.4609 | 0.4609 | 0.4611 |
| 2020-06-24 16:26:15 | 2020-06-24 16:30:00 | 0.4600 | 0.4600 | 0.4602 | 0.4604 | 0.4608 | 0.4609 | 0.4611 |
| 2020-06-24 16:18:44 | 2020-06-24 16:15:00 | 0.4598 | 0.4600 | 0.4602 | 0.4604 | 0.4609 | 0.4608 | 0.4612 |
| 2020-06-26 19:28:06 | 2020-06-26 19:30:00 | 0.4726 | 0.4727 | 0.4727 | 0.4727 | 0.4733 | 0.4727 | 0.4732 |
| collectDateTime | datetime | mean_abs350 | abs350_ma01 | abs350_ma03 | abs350_ma04 | abs350_ma04u | abs350_ma06 | abs350_ma12 |
|---|---|---|---|---|---|---|---|---|
| 2020-06-24 17:36:27 | 2020-06-24 17:30:00 | 0.0449 | 0.0450 | 0.0452 | 0.0452 | 0.0455 | 0.0457 | 0.0456 |
| 2020-06-24 16:26:15 | 2020-06-24 16:30:00 | 0.0449 | 0.0447 | 0.0448 | 0.0450 | 0.0453 | 0.0455 | 0.0457 |
| 2020-06-24 16:18:44 | 2020-06-24 16:15:00 | 0.0443 | 0.0447 | 0.0447 | 0.0450 | 0.0453 | 0.0454 | 0.0458 |
| 2020-06-26 19:28:06 | 2020-06-26 19:30:00 | 0.0545 | 0.0548 | 0.0548 | 0.0548 | 0.0550 | 0.0548 | 0.0554 |
This is the availability of SUNA data for AOS sampling dates
| aos_datetime | check_3day | check_1day | check_6hr | check_1hr |
|---|---|---|---|---|
| 2016-10-19 15:30:00 | FALSE | FALSE | FALSE | FALSE |
| 2016-11-16 16:00:00 | FALSE | FALSE | FALSE | FALSE |
| 2016-12-19 17:53:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-01-18 16:15:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-02-13 16:15:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-03-22 14:45:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-04-12 15:15:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-05-03 14:20:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-06-08 14:45:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-07-06 15:00:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-08-03 14:50:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-09-06 14:15:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-10-19 15:00:00 | FALSE | FALSE | FALSE | FALSE |
| 2017-11-01 15:15:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-01-04 17:00:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-02-13 16:45:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-03-13 16:05:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-04-17 16:03:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-05-01 16:26:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-06-05 15:40:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-07-05 15:20:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-08-07 16:16:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-09-04 15:50:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-10-16 16:03:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-10-30 16:07:00 | FALSE | FALSE | FALSE | FALSE |
| 2018-12-04 16:42:00 | FALSE | FALSE | FALSE | FALSE |
| 2019-01-10 17:10:00 | FALSE | FALSE | FALSE | FALSE |
| 2019-02-11 17:55:00 | FALSE | FALSE | FALSE | FALSE |
| 2019-03-26 16:10:00 | FALSE | FALSE | FALSE | FALSE |
| 2019-05-07 16:10:00 | FALSE | FALSE | FALSE | FALSE |
| 2019-06-04 15:25:00 | FALSE | FALSE | FALSE | FALSE |
| 2019-07-01 14:53:00 | TRUE | TRUE | TRUE | TRUE |
| 2019-08-06 15:55:00 | TRUE | TRUE | TRUE | TRUE |
| 2019-09-04 16:00:00 | TRUE | TRUE | TRUE | TRUE |
| 2019-10-16 17:05:00 | TRUE | TRUE | TRUE | TRUE |
| 2019-12-04 17:40:00 | FALSE | FALSE | FALSE | FALSE |
| 2020-08-04 15:07:00 | FALSE | FALSE | FALSE | FALSE |
| 2020-09-02 13:27:00 | FALSE | FALSE | FALSE | FALSE |
| 2021-01-07 16:08:00 | FALSE | FALSE | FALSE | FALSE |
| 2021-02-02 17:15:00 | FALSE | FALSE | FALSE | FALSE |
| 2021-03-02 18:05:00 | FALSE | FALSE | FALSE | FALSE |
| 2021-04-07 15:45:00 | TRUE | FALSE | FALSE | FALSE |
| 2021-05-04 15:22:00 | TRUE | TRUE | TRUE | TRUE |
| aos_datetime | check_3day | check_1day | check_6hr | check_1hr |
|---|---|---|---|---|
| 2019-07-01 14:53:00 | TRUE | TRUE | TRUE | TRUE |
| 2019-08-06 15:55:00 | TRUE | TRUE | TRUE | TRUE |
| 2019-09-04 16:00:00 | TRUE | TRUE | TRUE | TRUE |
| 2019-10-16 17:05:00 | TRUE | TRUE | TRUE | TRUE |
| 2021-04-07 15:45:00 | TRUE | FALSE | FALSE | FALSE |
| 2021-05-04 15:22:00 | TRUE | TRUE | TRUE | TRUE |
Helper table for manually pulling SUNA data (AOS dates):
| aos_datetime | check_1day | interval3_start | interval3_end |
|---|---|---|---|
| 2019-07-01 14:53:00 | TRUE | 2019-06-28 | 2019-07-04 |
| 2019-08-06 15:55:00 | TRUE | 2019-08-03 | 2019-08-09 |
| 2019-09-04 16:00:00 | TRUE | 2019-09-01 | 2019-09-07 |
| 2019-10-16 17:05:00 | TRUE | 2019-10-13 | 2019-10-19 |
| 2021-04-07 15:45:00 | FALSE | 2021-04-04 | 2021-04-10 |
| 2021-05-04 15:22:00 | TRUE | 2021-05-01 | 2021-05-07 |
NEON-processed/suna-L0-timeseriesRegression for sensor data within the same day
## `geom_smooth()` using formula 'y ~ x'